摘要
用模式识别和人工神经网络在多个无量纲数张成的多维空间中处理反应过程的实测数据,以探讨合成氨和SO2产率的主要影响因素.
Using the multi-dimensional spaces spanned by the dimensionless numbers describing the similarity of complicated chemical reaction systems, the macroscopic kinetics data are analysed by pattern recognition and artificial neural network. The regularities found are useful for industrial optimization and mechanism study. As examples of application of these methods, the kinetics of NH3 synthesis and SO2 Oxidation are studied in this paper.
出处
《计算机与应用化学》
CAS
CSCD
1997年第4期296-298,共3页
Computers and Applied Chemistry
关键词
合成氨
无量纲数
模式识别
二氧化硫
产率
Ammonia synthesis, Dimensionless numbers, Pattern recognition